This tutorial is an introduction to Bayesian statistics using Python. My goal is to help participants understand the concepts and solve real problems. We will use material from my book, Think Stats: Probability and Statistics for Programmers (O’Reilly Media).

Social Network data permeates our world -- yet we often don't know what to do with it. In this tutorial, I will introduce both theory and practice of Social Network Analysis -- gathering, analyzing and visualizing data using Python and other open-source tools. I will walk the attendees through an entire project, from gathering and cleaning data to presenting results.

This tutorial will walk the attendees from some introductory game development theory (what makes a good game) and through development of a simple game (how to make a good game) with time left over for some experimentation and exploration of different types of games.

From how the operating system handles your requests through design principles on how to use concurrency and parallelism to optimize your program's performance and scalability. We will cover processes, threads, generators, coroutines, non-blocking IO, and the gevent library.

Learn how to build fast and interactive web applications using a wsgi compliant web framework and co-routines.
Utilizing Redis/ZeroMQ, Socket.IO, and GEvent you will learn how to build a responsive and concurrent web app while maintaining good test coverage.

IPython provides tools for interactive and parallel computing that are widely used in scientific computing, but can benefit any Python developer.
We will show how to use IPython in different ways, as: an interactive shell, an embedded shell, a graphical console, a network-aware VM in GUIs, a web-based notebook with code, graphics and rich HTML, and a high-level framework for parallel computing.

Are you interested in learning more about Music but have found most material to be kind of patronizing or to present things magically instead of logically? The good news is that much of music can be understood with programming and math, two things you're already good at! In this hands-on workshop you'll learn some elements of music from a (Python) programmer's perspective.

Pyramid is the web framework at the core of the Pylons Project. It's a "pay only for what you eat" framework. You can get started easily and learn new concepts as you go, and only if you need them. It's simple, well tested, well documented, and fast. This course will present Pyramid and lead you through the creation of a an application as the concepts from the framework are introduced.

This intermediate-level class will teach you techniques using the popular NoSQL database MongoDB, its driver PyMongo, and the object-document mapper Ming to write maintainable, high-performance, and scalable applications. We will cover everything you need to become an effective Ming/MongoDB developer from basic PyMongo queries to high-level object-document mapping setups in Ming.

The goal of this tutorial is to give the attendee a first experience of machine learning tools applied to practical software engineering tasks such as language detection of tweets, topic classification of web pages, sentiment analysis of customer products reviews and facial recognition in pictures from the web or from your own webcam.

Learn the basics of natural language processing with NLTK, the Natural Language ToolKit. First we'll cover tokenization, stemming and wordnet. Next we'll get into part-of-speech tagging, chunking & named entity recognition. Then we'll close with text classification and sentiment analysis. You'll walk out with new super-powers and an appreciation of the difficulties of analyzing human language.

We're going to mesh TDD, a desire to learn Python and Brazilian BBQ. Bring your laptop (having Python 2.x installed (will note 3.x differences)). This is hands on! You will program! It is assumed that you know how to program but perhaps not in Python. You start hungry and leave stuffed. We assume you know nothing and will stuff you with enough Python to be dangerous.

Are you new to Python and want to learn how to step it up to the next level? Have you wondered about functional programming, closures, decorators, context managers, generators or list comprehensions and when you should use them and how to test them? This hands-on tutorial will cover these intermediate subjects in detail, by explaining the theory behind them then walking through examples.

Graphs are a fundamental datatype - but typical developers don't get as much exposure to using and working with graphs as with other datatypes like tables and queues. This is a from-the-ground up working session; by the end, attendees should have the tools and experience to model and analyze problems with graphs.

This tutorial teaches students how to create beautiful, interactive maps for the web. When asked to display geodata, most developers decide to put some big red markers on an embeddable Google Map and call it a day. If you're interested in creating maps that are more beautiful, more interactive, and more usable, this tutorial is for you.

When it comes to plotting with Python many people think about matplotlib.
It is widely used and provides a simple interface for creating a wide variety
of plots from very simple diagrams to sophisticated animations.
This tutorial is a hands-on introduction that teaches the basics of matplotlib.
Students will learn how to create publication-ready plots with just a few lines
of Python.

For many applications PyPy can provide performance benefits right out of the box. However, little details can push your application to perform much better. In this tutorial we'll give you insights on how to push pypy to it's limites. We'll focus on understanding the performance characteristics of PyPy, and learning the analysis tools in order to maximize your applications performance.

This tutorial provides an overview of techniques to improve the performance of Python programs. The focus is on concepts such as profiling, difference of data structures and algorithms as well as a selection of tools and libraries that help to speed up Python.

This tutorial is for software developers who've been using Python with success for a while but are looking for a deeper understanding of the language. It demystifies a number of language features that are often misunderstood.

The world of infrastructure as code is becoming far more pervasive and many Python developers are trying to find a way to get started. This class will get you up and running with Chef and Fabric to manage your systems be they in the cloud or under your desk.

Exciting information is trapped in web pages and behind HTML forms. In this tutorial, you'll learn how to parse those pages and when to apply advanced techniques that make scraping faster and more stable.
We'll cover parallel downloading with Twisted, gevent, and others; analyzing sites behind SSL; driving JavaScript-y sites with Selenium; and evading common anti-scraping techniques.

The Django framework is a fast, flexible, easy to learn, and easy to use framework for designing and deploying web sites and services using Python. In this session, we'll cover the fundamentals of development with Django, generate a Django data model, and put together a simple web site using the framework.

In this tutorial, I will cover how to write very fast Python code for data analysis. I will briefly introduce NumPy and illustrate how fast code for Python is written in SciPy using tools like Fwrap / F2py and Cython. I will also describe interesting new approaches to creating fast code that is leading changes to NumPy on a fundamental level.

Relational databases are often the bread-and-butter of large-scale data storage, yet they are often poorly understood by Python programmers. Organizations even split programmers into SQL and front-end teams, each of which jealously guards its turf. These tutorials will take what you already know about Python programming, and advance into a new realm: SQL programming and database design.

Python projects can succeed or fail because of their documentation.
Thanks to Sphinx, Python now has a “documentation framework” with
indexing, syntax highlighting, and integration with your code.
Students will be given a small undocumented Python package,
and during the exercises they will give the package
a tutorial and reference manual.
Plus: deployment and theming!

This tutorial introduces programmers with a basic Python skills to the concepts
and techniques of event driven programming. The focus is on understanding an
event loop and handling the events related to TCP connections. Twisted is
introduced as a re-usable event loop implementation and the abstract concepts of
event driven programming are related to specific uses of the Twisted library.

Presents techniques and patterns for creating custom PyQt widgets easily. Focus is the separation of layout and logic to produce code that is easy to read and understand, and also inexpensive to maintain and evolve. Encourages and demonstrates the use of layout design applications, code generators and composition over inheritance. Based on PyQt4 but easily applicable to PySide as well.

The tutorial will give a hands-on introduction to manipulating and analyzing large and small structured data sets in Python using the pandas library. While the focus will be on learning the nuts and bolts of the library's features, I also aim to demonstrate a different way of thinking regarding structuring data in memory for manipulation and analysis.

A tutorial that goes beyond all other Django tutorials; we'll dive deep into the guts of the framework, and learn how each commonly-used component -- ORM, templates, HTTP handling, views and the admin -- work from the bottom up, covering both public and internal APIs in excruciating detail.